000075768 001__ 75768
000075768 005__ 20200813075838.0
000075768 0247_ $$2doi$$a10.3389/fpsyg.2018.02182
000075768 0248_ $$2sideral$$a108442
000075768 037__ $$aART-2018-108442
000075768 041__ $$aeng
000075768 100__ $$aLlorente, J.M.
000075768 245__ $$aVariability of the prevalence of depression in function of sociodemographic and environmental factors: ecological model
000075768 260__ $$c2018
000075768 5060_ $$aAccess copy available to the general public$$fUnrestricted
000075768 5203_ $$aMajor depression etiopathogenesis is related to a wide variety of genetics, demographic and psychosocial factors, as well as to environmental factors. The objective of this study is to analyze sociodemographic and environmental variables that are related to the prevalence of depression through correlation analysis and to develop a regression model that explains the behavior of this disease from an ecological perspective. This is an ecological, retrospective, cross-sectional study. The target population was 1,148,430 individuals over the age of 16 who were registered in Aragon (Spain) during 2010, with electronic medical records in the community’s primary health care centers. The spatial unit was the Basic Health Area (BHA). The dependent variable was the diagnosis of Depression and the ecological independent variables were: Demographic variables (gender and age), population distribution, typology of the entity, population structure by sex and age, by nationality, by education, by work, by salary, by marital status, structure of the household by number of members, and state of the buildings. The results show moderate and positive correlations with higher rates of depression in areas having a higher femininity index, higher population density, areas with a higher unemployment rate and higher average salary. The results of the linear regression show that aging +75 and rural entities act as protective factors for depression, while urban areas and deficient buildings act as risk factors. In conclusion, the ecological methodology may be a useful tool which, together with the statistical epidemiological analysis, can help in the political decision making process.
000075768 536__ $$9info:eu-repo/grantAgreement/ES/ISCIII/PS09-01378$$9info:eu-repo/grantAgreement/ES/DGA/B21-17R
000075768 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000075768 590__ $$a2.129$$b2018
000075768 591__ $$aPSYCHOLOGY, MULTIDISCIPLINARY$$b40 / 137 = 0.292$$c2018$$dQ2$$eT1
000075768 592__ $$a0.997$$b2018
000075768 593__ $$aPsychology (miscellaneous)$$c2018$$dQ1
000075768 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000075768 700__ $$0(orcid)0000-0001-6565-9699$$aOliván-Blázquez, B.$$uUniversidad de Zaragoza
000075768 700__ $$0(orcid)0000-0002-9541-5609$$aZuñiga-Antón, M.$$uUniversidad de Zaragoza
000075768 700__ $$0(orcid)0000-0001-9887-2250$$aMasluk, B.$$uUniversidad de Zaragoza
000075768 700__ $$aAndres, E.
000075768 700__ $$0(orcid)0000-0002-3797-4218$$aGarcia-Campayo, J.$$uUniversidad de Zaragoza
000075768 700__ $$0(orcid)0000-0002-5494-6550$$aMagallon-Botaya, R.$$uUniversidad de Zaragoza
000075768 7102_ $$14009$$2740$$aUniversidad de Zaragoza$$bDpto. Psicología y Sociología$$cÁrea Psicología Social
000075768 7102_ $$11007$$2610$$aUniversidad de Zaragoza$$bDpto. Medicina, Psiqu. y Derm.$$cArea Medicina
000075768 7102_ $$13006$$2435$$aUniversidad de Zaragoza$$bDpto. Geograf. Ordenac.Territ.$$cÁrea Geografía Humana
000075768 7102_ $$11007$$2745$$aUniversidad de Zaragoza$$bDpto. Medicina, Psiqu. y Derm.$$cArea Psiquiatría
000075768 7102_ $$14009$$2735$$aUniversidad de Zaragoza$$bDpto. Psicología y Sociología$$cÁrea Psicolog.Evolut.Educac
000075768 773__ $$g9 (2018), 2182 [10 pp.]$$pFront. psychol.$$tFrontiers in Psychology$$x1664-1078
000075768 8564_ $$s604801$$uhttps://zaguan.unizar.es/record/75768/files/texto_completo.pdf$$yVersión publicada
000075768 8564_ $$s22717$$uhttps://zaguan.unizar.es/record/75768/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
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000075768 951__ $$a2020-08-13-07:57:53
000075768 980__ $$aARTICLE